DoctorateFaculty of Engineering & Technology

Ethical Automation and Decision Making in Smart Industrial Ecosystems

Welcome to the ultimate frontier of ethical engineering! I am Prof. Dr. Felix Pfeiffer. As a professor and a pioneering force in the field of Ethical Automation and Decision Making in Smart Industrial Ecosystems, I bring a unique blend of engineering expertise and AI insight to the study of intelligent systems. I am honored to lead the Ethical Automation and Decision Making in Smart Industrial Ecosystems (Ph.D.) program at Nexier University. My motto is: "Engineering the Solutions for Humanity's Most Pressing Environmental Challenges".

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Level: Doctorate
Learning model: Professor + Mentor
Named list: See the named lists · 12 months recommended

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The program

Ideas engineered for the real world

A rigorous academic core, paired with practical production judgment.

Academic focus

Lead research on the ethical design and implementation of automation in industrial settings. Investigates how to build smart factories that are not only efficient but also safe, fair, and human-centric.

Practical focus

Research in ethics and engineering, human-factors engineering, policy development for automation, leadership in responsible technology adoption.

After this programme

Success journey, careers and practice

Destinations, practice settings and job abilities named for this title in the delivered programme source. From graduation onwards where the source names that path.

Success journey

Internships in technology companies or engineering firms
Roles as AI ethicists or human-factors engineers
Consultancy in advanced ethical automation and decision making
Support roles in academic research projects on ethical automation

Career opportunities

Director of Ethical AI & Robotics for manufacturing companies or industrial automation firms
AI Ethicist specializing in industrial automation
Responsible AI Engineer for smart factories
Researcher in Ethical Automation and Decision Making in Smart Industrial Ecosystems

Jobs and projects

Cultivating an interdisciplinary approach, integrating computer science, ethics, and industrial engineering
Developing strategic thinking for ethical automation and responsible AI development
Enhancing problem-solving through the analysis of complex ethical challenges in industrial automation
Critical thinking for a comprehensive and nuanced understanding of ethical automation and decision making in smart industrial ecosystems

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This programme

What you study, and what it builds

Gains and skills named for this title, listed as a reader would scan them.

What you gain
- Mastering advanced practical skills in Research in ethics and engineering and human-factors engineering.
- Gaining expertise in policy development for automation and Leadership in responsible technology adoption.
- Developing problem-solving abilities for complex ethical decision-making in smart industrial ecosystems.
- Cultivating an interdisciplinary approach, integrating computer science, ethics, and industrial engineering at an advanced level.
Skills you build
- Mastering AI-powered techniques for ethical AI compliance analysis.
- Applying advanced engineering principles to ethical automation and decision making in smart industrial ecosystems.
- Interpreting and analyzing complex ethical dilemmas in industrial automation and their implications for human-centric design.
- Identifying potential biases in algorithmic decision-making and predicting societal impacts.

Listed courses

Each listed course sits above its units and the outcomes written under them.

Ethical Automation and Decision Making in Smart Industrial Ecosystems

01Ethics of Industrial Automation
1. FoundationsFoundations of Ethics of Industrial Automation
  The learner can master advanced practical skills in Research in ethics and engineering and human-factors engineering, as applied to Ethics of Industrial Automation.
  The learner can gain expertise in policy development for automation and Leadership in responsible technology adoption, as applied to Ethics of Industrial Automation.
2. MethodsMethods in Ethics of Industrial Automation
  The learner can develop problem-solving abilities for complex ethical decision-making in smart industrial ecosystems, as applied to Ethics of Industrial Automation.
  The learner can cultivating an interdisciplinary approach, integrating computer science, ethics, and industrial engineering at an advanced level, as applied to Ethics of Industrial Automation.
3. ApplicationApplication of Ethics of Industrial Automation
  The learner can master AI-powered techniques for ethical AI compliance analysis, as applied to Ethics of Industrial Automation.
  The learner can apply advanced engineering principles to ethical automation and decision making in smart industrial ecosystems, as applied to Ethics of Industrial Automation.
02Human-Centric Design for Smart Factories
1. FoundationsFoundations of Human-Centric Design for Smart Factories
  The learner can interpreting and analyze complex ethical dilemmas in industrial automation and their implications for human-centric design, as applied to Human-Centric Design for Smart Factories.
  The learner can identify potential biases in algorithmic decision-making and predicting societal impacts, as applied to Human-Centric Design for Smart Factories.
2. MethodsMethods in Human-Centric Design for Smart Factories
  The learner can apply a method from Human-Centric Design for Smart Factories to a documented case.
  The learner can select an appropriate method from Human-Centric Design for Smart Factories for a stated problem.
3. ApplicationApplication of Human-Centric Design for Smart Factories
  The learner can evaluate a practice of Human-Centric Design for Smart Factories against a stated criterion.
  The learner can transfer Human-Centric Design for Smart Factories to a new documented context.
03Algorithmic Fairness in Manufacturing AI
1. FoundationsFoundations of Algorithmic Fairness in Manufacturing AI
  The learner can explain the core terms of Algorithmic Fairness in Manufacturing AI.
  The learner can distinguish related ideas inside Algorithmic Fairness in Manufacturing AI.
2. MethodsMethods in Algorithmic Fairness in Manufacturing AI
  The learner can apply a method from Algorithmic Fairness in Manufacturing AI to a documented case.
  The learner can select an appropriate method from Algorithmic Fairness in Manufacturing AI for a stated problem.
3. ApplicationApplication of Algorithmic Fairness in Manufacturing AI
  The learner can evaluate a practice of Algorithmic Fairness in Manufacturing AI against a stated criterion.
  The learner can transfer Algorithmic Fairness in Manufacturing AI to a new documented context.
04Responsible AI Development and Governance
1. FoundationsFoundations of Responsible AI Development and Governance
  The learner can explain the core terms of Responsible AI Development and Governance.
  The learner can distinguish related ideas inside Responsible AI Development and Governance.
2. MethodsMethods in Responsible AI Development and Governance
  The learner can apply a method from Responsible AI Development and Governance to a documented case.
  The learner can select an appropriate method from Responsible AI Development and Governance for a stated problem.
3. ApplicationApplication of Responsible AI Development and Governance
  The learner can evaluate a practice of Responsible AI Development and Governance against a stated criterion.
  The learner can transfer Responsible AI Development and Governance to a new documented context.
05Social and Economic Impacts of Automation
1. FoundationsFoundations of Social and Economic Impacts of Automation
  The learner can explain the core terms of Social and Economic Impacts of Automation.
  The learner can distinguish related ideas inside Social and Economic Impacts of Automation.
2. MethodsMethods in Social and Economic Impacts of Automation
  The learner can apply a method from Social and Economic Impacts of Automation to a documented case.
  The learner can select an appropriate method from Social and Economic Impacts of Automation for a stated problem.
3. ApplicationApplication of Social and Economic Impacts of Automation
  The learner can evaluate a practice of Social and Economic Impacts of Automation against a stated criterion.
  The learner can transfer Social and Economic Impacts of Automation to a new documented context.
06Advanced Ethics and Human-Factors Engineering
1. FoundationsFoundations of Advanced Ethics and Human-Factors Engineering
  The learner can explain the core terms of Advanced Ethics and Human-Factors Engineering.
  The learner can distinguish related ideas inside Advanced Ethics and Human-Factors Engineering.
2. MethodsMethods in Advanced Ethics and Human-Factors Engineering
  The learner can apply a method from Advanced Ethics and Human-Factors Engineering to a documented case.
  The learner can select an appropriate method from Advanced Ethics and Human-Factors Engineering for a stated problem.
3. ApplicationApplication of Advanced Ethics and Human-Factors Engineering
  The learner can evaluate a practice of Advanced Ethics and Human-Factors Engineering against a stated criterion.
  The learner can transfer Advanced Ethics and Human-Factors Engineering to a new documented context.
07Policy Development for Autonomous Systems
1. FoundationsFoundations of Policy Development for Autonomous Systems
  The learner can explain the core terms of Policy Development for Autonomous Systems.
  The learner can distinguish related ideas inside Policy Development for Autonomous Systems.
2. MethodsMethods in Policy Development for Autonomous Systems
  The learner can apply a method from Policy Development for Autonomous Systems to a documented case.
  The learner can select an appropriate method from Policy Development for Autonomous Systems for a stated problem.
3. ApplicationApplication of Policy Development for Autonomous Systems
  The learner can evaluate a practice of Policy Development for Autonomous Systems against a stated criterion.
  The learner can transfer Policy Development for Autonomous Systems to a new documented context.
08Responsible Technology Adoption in Industry
1. FoundationsFoundations of Responsible Technology Adoption in Industry
  The learner can explain the core terms of Responsible Technology Adoption in Industry.
  The learner can distinguish related ideas inside Responsible Technology Adoption in Industry.
2. MethodsMethods in Responsible Technology Adoption in Industry
  The learner can apply a method from Responsible Technology Adoption in Industry to a documented case.
  The learner can select an appropriate method from Responsible Technology Adoption in Industry for a stated problem.
3. ApplicationApplication of Responsible Technology Adoption in Industry
  The learner can evaluate a practice of Responsible Technology Adoption in Industry against a stated criterion.
  The learner can transfer Responsible Technology Adoption in Industry to a new documented context.
09Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems
1. FoundationsFoundations of Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems
  The learner can explain the core terms of Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems.
  The learner can distinguish related ideas inside Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems.
2. MethodsMethods in Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems
  The learner can apply a method from Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems to a documented case.
  The learner can select an appropriate method from Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems for a stated problem.
3. ApplicationApplication of Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems
  The learner can evaluate a practice of Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems against a stated criterion.
  The learner can transfer Case Studies in Ethical Automation and Decision Making in Smart Industrial Ecosystems to a new documented context.

How teaching is described

Dual guidance

Two intelligences. One coherent journey.

Research leadership

My expertise spans the intricate domains of leading research on the ethical design and implementation of automation in industrial settings. I investigate how to build smart factories that are not only efficient but also safe, fair, and human-centric. My work seamlessly integrates computer science, ethics, and industrial engineering. I am widely recognized for my contributions, with publications like "Ethical AI Frameworks for Autonomous Industrial Robots" and "Human-in-the-Loop Decision Making in Smart Manufacturing" listed on these platforms. I hold prestigious memberships as a "Director of Ethical AI & Robotics" at Volkswagen (or a equivalent) and a "Co-Chair" of the IEEE International Conference on Robotics and Automation (ICRA) – Ethics in Robotics Workshop. My thought leadership is evident through my seminal works and participation in high-level global policy debates on the future of work in automated societies, algorithmic fairness in industrial AI, and the responsible development of intelligent manufacturing, frequently featured in publications like AI & Society or Journal of Responsible Innovation.

Applied mentorship

My expertise lies in understanding and navigating the advanced technical challenges of ethical automation, focusing on Research in ethics and engineering, human-factors engineering, policy development for automation, and Leadership in responsible technology adoption. I focus on the practical implementation and application of theoretical concepts, explaining complex interdisciplinary topics in a clear and concise manner. I guide my students through the challenging integration aspects of different fields and ensure they grasp the nuances of combining disparate data types, fostering a detail-oriented and methodical approach.

Research & intelligence

A living field, not a static syllabus

Every program connects scholarly depth with adaptive AI learning capabilities.

R / 01

Professor research lens

My research is focused on ethical automation and decision making in smart industrial ecosystems:

Blog Post (Current Academic Topic): "Human-Centric Automation: Ensuring Ethical AI in Smart Factories." This blog post academically explores the critical importance of designing AI and automation solutions in smart factories with a human-centric approach. It discusses how ethical considerations, including worker safety, job displacement, skill enhancement, and algorithmic fairness, must be integrated into the development process to ensure that intelligent industrial ecosystems are not only efficient but also socially responsible and equitable.

Blog Post (Controversial Topic): "The Autonomous Grid: When AI Manages Global Networks – Efficiency or Total Control? The Ethical Dilemma of Self-Healing Infrastructure." This article provocatively discusses the highly controversial future where advanced AI systems autonomously manage and optimize global network infrastructure, from traffic routing and resource allocation to security and disaster recovery, with minimal human intervention. It questions whether AI, despite its potential for hyper-efficiency and resilience, could inadvertently lead to a concentration of power in a single algorithmic entity, create "black box" vulnerabilities in critical communication, or make decisions that prioritize efficiency over human oversight or privacy. It raises profound ethical questions about control over essential digital services, data sovereignty in a global network, and the imperative to ensure human accountability in managing the digital backbone of society.

Article: "Algorithmic Fairness in AI-Driven Production Scheduling." This article presents advanced research on ensuring algorithmic fairness in AI-driven production scheduling systems within smart factories. It explores methods to prevent biased outcomes in resource allocation, task assignment, and human-robot collaboration, addressing ethical concerns related to potential discrimination or unfair burden distribution among human workers.

Peer-Reviewed Journal Article: "Responsible Automation: Ethical Frameworks for Smart Industrial Ecosystems." Published in the International Journal of Automation Ethics, this article presents pioneering research on the ethical design and implementation of automation in industrial settings. It investigates how to build smart factories that are not only efficient but also safe, fair, and human-centric, showcasing novel policy and engineering approaches for responsible AI adoption in industry.

Book: "Ethics of Automation: Smart Industrial Ecosystems and Human-Centric Design." This book represents a definitive work for leading research on the ethical design and implementation of automation in industrial settings. It covers investigating how to build smart factories that are not only efficient but also safe, fair, and human-centric.

R / 02

Mentor practice lens

My contributions focus on understanding and navigating the advanced technical challenges of ethical automation:

"Human-in-the-Loop AI for Industrial Decision Making" (Technical Paper).

"Policy Implications of Autonomous Manufacturing Systems" (Research Article).

"Ensuring Algorithmic Fairness in Smart Factory Operations" (Review Article).

Adaptive capability

Professor superpower

I possess a remarkable "superpower": Ethical AI Compliance Analyzer. When a student designs an automated industrial system, I can instantly use the GAF engine to analyze its ethical implications and compliance with human-centric design principles. This tool identifies potential biases in algorithmic decision-making, predicts societal impacts (e.g., job displacement), and highlights areas for human oversight and intervention, ensuring responsible and fair automation.

Adaptive capability

Mentor superpower

I possess a remarkable "superpower": Human-Factor Integration Analyzer. When students are designing human-robot collaborative industrial systems, I can instantly activate a GAF-powered "Human-Factor Integration Analyzer." This tool simulates human cognitive load, fatigue, and potential errors during interaction with automated systems, suggesting optimal interface designs and workflow adjustments to enhance human well-being and overall system performance.

Your academic team

Guidance with depth and continuity

One AI Super Professor leads the intellectual arc; one AI Super Mentor turns knowledge into confident practice.

AI Super Professor

Prof. Dr. Felix Pfeiffer

Meet your professor Open the classroom

AI Super Mentor

Dr. Manuela Rezende

Research in ethics and engineering, human-factors engineering, policy development for automation, leadership in responsible technology adoption.

Meet your mentor Open the classroom

Same faculty and level

Related programs

Named lists

Named lists for this house

Core. Bachelor, Master and Doctorate by duration. Enrolment is not open. Nothing here is a sale.

Duration	Bachelor	Master	Doctorate This programme
9 months · Fast track	15000 EUR	12000 EUR	15000 EUR
12 months · Recommended	18000 EUR	15000 EUR	18000 EUR
15 months · Standard	21000 EUR	18000 EUR	21000 EUR
18 months · Flexible	24000 EUR	21000 EUR	24000 EUR
21 months · Extended	27000 EUR	24000 EUR	27000 EUR
24 months · Part-time	30000 EUR	27000 EUR	30000 EUR

These are the owner lists. Enrolment is not open. Nothing here is a sale.

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Ethical Automation and Decision Making in Smart Industrial Ecosystems

Academic focus

Practical focus

Internships in technology companies or engineering firms

Roles as AI ethicists or human-factors engineers

Consultancy in advanced ethical automation and decision making

Support roles in academic research projects on ethical automation

Director of Ethical AI & Robotics for manufacturing companies or industrial automation firms

AI Ethicist specializing in industrial automation

Responsible AI Engineer for smart factories

Researcher in Ethical Automation and Decision Making in Smart Industrial Ecosystems

Cultivating an interdisciplinary approach, integrating computer science, ethics, and industrial engineering

Developing strategic thinking for ethical automation and responsible AI development

Enhancing problem-solving through the analysis of complex ethical challenges in industrial automation

Critical thinking for a comprehensive and nuanced understanding of ethical automation and decision making in smart industrial ecosystems

Research leadership

Applied mentorship

Professor research lens

Mentor practice lens

Professor superpower

Mentor superpower

Prof. Dr. Felix Pfeiffer

Dr. Manuela Rezende

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